Virtual Reality: Beyond Visualization

Virtual reality (VR) has recently become an affordable technology. A wide range of options are available to access this unique visualization medium, from simple cardboard inserts for smartphones to truly advanced headsets tracked by external sensors. While it is now possible for any research team to gain access to VR, we can still question what it brings to scientific research. Visualization and the ability to navigate complex three-dimensional data are undoubtedly a gateway to many scientific applications; however, we are convinced that data treatment and numerical simulations, especially those mixing interactions with data, human cognition, and automated algorithms will be the future of VR in scientific research. Moreover, VR might soon merit the same level of attention to imaging data as machine learning currently has. In this short perspective, we discuss approaches that employ VR in scientific research based on some concrete examples.     

Complex Contagion of Campaign Donations

Money is central in US politics, and most campaign contributions stem from a tiny, wealthy elite. Like other political acts, campaign donations are known to be socially contagious. We study how campaign donations diffuse through a network of more than 50000 elites and examine how connectivity among previous donors reinforces contagion. We find that the diffusion of donations is driven by independent reinforcement contagion: people are more likely to donate when exposed to donors from different social groups than when they are exposed to equally many donors from the same group. Counter-intuitively, being exposed to one side may increase donations to the other side. Although the effect is weak, simultaneous cross-cutting exposure makes donation somewhat less likely. Finally, the independence of donors in the beginning of a campaign predicts the amount of money that is raised throughout a campaign. We theorize that people infer population-wide estimates from their local observations, with elites assessing the viability of candidates, possibly opposing candidates in response to local support. Our findings suggest that theories of complex contagions need refinement and that political campaigns should target multiple communities.     

Contagion of Cooperation in Static and Fluid Social Networks

Cooperation is essential for successful human societies. Thus, understanding how cooperative and selfish behaviors spread from person to person is a topic of theoretical and practical importance. Previous laboratory experiments provide clear evidence of social contagion in the domain of cooperation, both in fixed networks and in randomly shuffled networks, but leave open the possibility of asymmetries in the spread of cooperative and selfish behaviors. Additionally, many real human interaction structures are dynamic: we often have control over whom we interact with. Dynamic networks may differ importantly in the goals and strategic considerations they promote, and thus the question of how cooperative and selfish behaviors spread in dynamic networks remains open. Here, we address these questions with data from a social dilemma laboratory experiment. We measure the contagion of both cooperative and selfish behavior over time across three different network structures that vary in the extent to which they afford individuals control over their network ties. We find that in relatively fixed networks, both cooperative and selfish behaviors are contagious. In contrast, in more dynamic networks, selfish behavior is contagious, but cooperative behavior is not: subjects are fairly likely to switch to cooperation regardless of the behavior of their neighbors. We hypothesize that this insensitivity to the behavior of neighbors in dynamic networks is the result of subjects’ desire to attract new cooperative partners: even if many of one’s current neighbors are defectors, it may still make sense to switch to cooperation. We further hypothesize that selfishness remains contagious in dynamic networks because of the well-documented willingness of cooperators to retaliate against selfishness, even when doing so is costly. These results shed light on the contagion of cooperative behavior in fixed and fluid networks, and have implications for influence-based interventions aiming at increasing cooperative behavior.     

The Social Contagion Effect of Marijuana Use among Adolescents

Background

Research on adolescent substance use has consistently identified a strong relationship between adolescent behavior and the behavior of their peers. However, peer effects are difficult to estimate and causal interpretations must be undertaken with caution since individuals in most cases choose with whom to associate. In this paper we seek to empirically quantify the causal role of peer social networks in explaining marijuana usage among adolescents.

Methods and Findings

Using data from a nationally representative sample of adolescents we utilize a multivariate structural model with school-level fixed effects to account for the problems of contextual effects, correlated effects and peer selections to purge the potential biases from the estimates of peer influence. Our peer group measures are drawn not only from the nomination of close friends (N = 6,377), but also from classmates (N = 19,335). Marijuana usage among the peer groups were constructed using the peers'' own report of their marijuana consumption. Controlling for parent level characteristics, and other demographic parameters, we find that a 10% increase in the proportion of close friends and classmates who use marijuana increases the probability that an individual chooses to use marijuana by 5%.

Conclusion

Our findings indicate that peer effects are important determinants of marijuana use even after controlling for potential biases We also found evidence to show that the influence of close friends and the more exogenous classmates are quite similar in magnitude under our preferred specification, supporting theory predicting the importance of peer influence. Effective policy aimed at reducing marijuana usage among adolescents would consider these significant peer effects.     

Quantification of Social Behavior in D. discoideum Reveals Complex Fixed and Facultative Strategies

Understanding the maintenance of cooperation requires an understanding of the nature of cheaters and the strategies used to mitigate their effects. However, it is often difficult to determine how cheating or differential social success has arisen. For example, cheaters may employ different strategies (e.g., fixed and facultative), whereas other causes of unequal fitness in social situations can result in winners and losers without cheating. To address these problems, we quantified the social success of naturally occurring genotypes of Dictyostelium discoideum during the formation of chimeric fruiting bodies, consisting of dead stalk cells and viable spores. We demonstrate that an apparent competitive dominance hierarchy of spore formation in chimera is partly due to a fixed strategy where genotypes exhibit dramatically different spore allocations. However, we also find complex, variable facultative strategies, where genotypes change their allocation in chimera. By determining the magnitude and direction of these changes, we partition facultative cheating into two forms: (1) promotion of individual fitness through selfish behaviour (“self-promotion”) and (2) coercion of other genotypes to act cooperatively. Our results demonstrate and define social interactions between D. discoideum isolates, thus providing a conceptual framework for the study of the genetic mechanisms that underpin social evolution.     

Feeding and Stocking Up: Radio-Labelled Food Reveals Exchange Patterns in Ants

Food sharing is vital for a large number of species, either solitary or social, and is of particular importance within highly integrated societies, such as in colonial organisms and in social insects. Nevertheless, the mechanisms that govern the distribution of food inside a complex organizational system remain unknown.Using scintigraphy, a method developed for medical imaging, we were able to describe the dynamics of food-flow inside an ant colony. We monitored the sharing process of a radio-labelled sucrose solution inside a nest of Formica fusca. Our results show that, from the very first load that enters the nest, food present within the colony acts as negative feedback to entering food. After one hour of the experiments, 70% of the final harvest has already entered the nest. The total foraged quantity is almost four times smaller than the expected storage capacity. A finer study of the spatial distribution of food shows that although all ants have been fed rapidly (within 30 minutes), a small area representing on average 8% of the radioactive surface holds more than 25% of the stored food. Even in rather homogeneous nests, we observed a strong concentration of food in few workers. Examining the position of these workers inside the nest, we found heavily loaded ants in the centre of the aggregate. The position of the centre of this high-intensity radioactive surface remained stable for the three consecutive hours of the experiments.We demonstrate that the colony simultaneously managed to rapidly feed all workers (200 ants fed within 30 minutes) and build up food stocks to prevent food shortage, something that occurs rather often in changing environments. Though we expected the colony to forage to its maximum capacity, the flow of food entering the colony is finely tuned to the colony''s needs. Indeed the food-flow decreases proportionally to the food that has already been harvested, liberating the work-force for other tasks.     

The Impact of Heterogeneous Thresholds on Social Contagion with Multiple Initiators

The threshold model is a simple but classic model of contagion spreading in complex social systems. To capture the complex nature of social influencing we investigate numerically and analytically the transition in the behavior of threshold-limited cascades in the presence of multiple initiators as the distribution of thresholds is varied between the two extreme cases of identical thresholds and a uniform distribution. We accomplish this by employing a truncated normal distribution of the nodes’ thresholds and observe a non-monotonic change in the cascade size as we vary the standard deviation. Further, for a sufficiently large spread in the threshold distribution, the tipping-point behavior of the social influencing process disappears and is replaced by a smooth crossover governed by the size of initiator set. We demonstrate that for a given size of the initiator set, there is a specific variance of the threshold distribution for which an opinion spreads optimally. Furthermore, in the case of synthetic graphs we show that the spread asymptotically becomes independent of the system size, and that global cascades can arise just by the addition of a single node to the initiator set.     

The Influence of Social Systems on Patterns of Mitochondrial DNA Variation in Baboons

Behavior is influenced by genes but can also shape the genetic structure of natural populations. Investigating this link is of great importance because behavioral processes can alter the genetic diversity on which selection acts. Gene flow is one of the main determinants of the genetic structure of a population and dispersal is the behavior that mediates gene flow. Baboons (genus Papio) are among the most intensely studied primate species and serve as a model system to investigate the evolution of social systems using a comparative approach. The general mammalian pattern of male dispersal and female philopatry has thus far been found in baboons, with the exception of hamadryas baboons (Papio hamadryas). As yet, the lack of data on Guinea baboons (Papio papio) creates a taxonomic gap in genus-wide comparative analyses. In our study we investigated the sex-biased dispersal pattern of Guinea baboons in comparison to hamadryas, olive, yellow, and chacma baboons using sequences of the maternally transmitted mitochondrial hypervariable region I. Analyzing whole-range georeferenced samples (N = 777), we found strong evidence for female-biased gene flow in Guinea baboons and confirmed this pattern for hamadryas baboons, as shown by a lack of genetic-geographic structuring. In addition, most genetic variation was found within and not among demes, in sharp contrast to the pattern observed in matrilocal primates including the other baboon taxa. Our results corroborate the notion that the Guinea baboons’ social system shares some important features with that of hamadryas baboons, suggesting similar evolutionary forces have acted to distinguish them from all other baboons.     

Beyond Corroboration: Strengthening Model Validation by Looking for Unexpected Patterns

Models of emergent phenomena are designed to provide an explanation to global-scale phenomena from local-scale processes. Model validation is commonly done by verifying that the model is able to reproduce the patterns to be explained. We argue that robust validation must not only be based on corroboration, but also on attempting to falsify the model, i.e. making sure that the model behaves soundly for any reasonable input and parameter values. We propose an open-ended evolutionary method based on Novelty Search to look for the diverse patterns a model can produce. The Pattern Space Exploration method was tested on a model of collective motion and compared to three common a priori sampling experiment designs. The method successfully discovered all known qualitatively different kinds of collective motion, and performed much better than the a priori sampling methods. The method was then applied to a case study of city system dynamics to explore the model’s predicted values of city hierarchisation and population growth. This case study showed that the method can provide insights on potential predictive scenarios as well as falsifiers of the model when the simulated dynamics are highly unrealistic.     

Data Mining of Toxic Chemicals: Structure Patterns and QSAR

We take a two-step strategy to explore noncongeneric toxic chemicals from the database RTECS: the screening of structure patterns and the generation of a detailed relationship between structure and activity. An efficient similarity comparison is proposed to screen chemical patterns for further QSAR analysis. Then CoMFA study is carried out on one structure pattern as an example of the implementation, and the result shows that QSAR studies of structure patterns can provide an estimate of the activity as well as a detailed relationship between activity and structure. From the performance of overall procedure, such a stepwise scheme is demonstrated to be feasible and effective to mine a database of toxic chemicals.     

Looking Reality in the Eye: Museums and Social Responsibility

Looking Reality in the Eye: Museums and Social Responsibility . Robert P. Janesand Gerald T. Conaty, eds. Calgary: University of Calgary Press, 2005. 196 pp.     

Cryo-electron Microscopy Reveals the Structure of the Nuclear Pore Complex

The nuclear pore complex (NPC) is a giant protein assembly that penetrates the double layers of the nuclear membrane. The overall structure of the NPC has approximately eightfold symmetry and is formed by approximately 30 nucleoporins. The great size and complexity of the NPC have hindered the study of its structure for many years until recent breakthroughs were achieved by integrating the latest high-resolution cryo-electron microscopy (cryo-EM), the emerging artificial intelligence-based modeling and all other available structural information from crystallography and mass spectrometry. Here, we review our latest knowledge of the NPC architecture and the history of its structural study from in vitro to in situ with progressively improved resolutions by cryo-EM, with a particular focus on the latest subnanometer-resolution structural studies. The future directions for structural studies of NPCs are also discussed.     

Acoustic Telemetry Reveals Large-Scale Migration Patterns of Walleye in Lake Huron

Fish migration in large freshwater lacustrine systems such as the Laurentian Great Lakes is not well understood. The walleye (Sander vitreus) is an economically and ecologically important native fish species throughout the Great Lakes. In Lake Huron walleye has recently undergone a population expansion as a result of recovery of the primary stock, stemming from changing food web dynamics. During 2011 and 2012, we used acoustic telemetry to document the timing and spatial scale of walleye migration in Lake Huron and Saginaw Bay. Spawning walleye (n = 199) collected from a tributary of Saginaw Bay were implanted with acoustic tags and their migrations were documented using acoustic receivers (n = 140) deployed throughout U.S. nearshore waters of Lake Huron. Three migration pathways were described using multistate mark-recapture models. Models were evaluated using the Akaike Information Criterion. Fish sex did not influence migratory behavior but did affect migration rate and walleye were detected on all acoustic receiver lines. Most (95%) tagged fish migrated downstream from the riverine tagging and release location to Saginaw Bay, and 37% of these fish emigrated from Saginaw Bay into Lake Huron. Remarkably, 8% of walleye that emigrated from Saginaw Bay were detected at the acoustic receiver line located farthest from the release location more than 350 km away. Most (64%) walleye returned to the Saginaw River in 2012, presumably for spawning. Our findings reveal that fish from this stock use virtually the entirety of U.S. nearshore waters of Lake Huron.